Using Machine Learning to Predict the Performance of Coal Ash in Concrete with Bulk Oxide Content

Using Machine Learning to Predict the Performance of Coal Ash in Concrete with the Bulk Oxide Content Presented By: Tyler Ley, Oklahoma State University Description: Coal ash is a valuable SCM for a concrete mixture. This presentation uses the bulk oxide content to predict the performance level of coal ash in concrete. The results from two different machine learning algorithms will be used. The first uses the bulk oxide content in a web interface and the second algorithm develops a simple set of look up tables that can be used in guide or recommendation documents. These tools predict the compressive strength, resistivity, diffusion coefficient, and the amount of heat released during hydration. These promise to be simple and powerful tools to help the concrete industry better use coal ash and reclaimed coal ash in the future.